Differential gene expression profiles in human THP-1 monocytes treated with Lactobacillus plantarum or Staphylococcus aureus lipoteichoic acid

2011 ◽  
Vol 54 (5) ◽  
pp. 763-770 ◽  
Author(s):  
Ri-Zhong Zeng ◽  
Han Geun Kim ◽  
Na Ra Kim ◽  
Min Geun Gim ◽  
Mi Yeon Ko ◽  
...  
2011 ◽  
Vol 77 (10) ◽  
pp. 3406-3412 ◽  
Author(s):  
Gino Vrancken ◽  
Luc De Vuyst ◽  
Tom Rimaux ◽  
Joke Allemeersch ◽  
Stefan Weckx

ABSTRACTSourdough is a very competitive and challenging environment for microorganisms. Usually, a stable microbiota composed of lactic acid bacteria (LAB) and yeasts dominates this ecosystem. Although sourdough is rich in carbohydrates, thus providing an ideal environment for microorganisms to grow, its low pH presents a particular challenge. The nature of the adaptation to this low pH was investigated forLactobacillus plantarumIMDO 130201, an isolate from a laboratory wheat sourdough fermentation. Batch fermentations were carried out in wheat sourdough simulation medium, and total RNA was isolated from mid-exponential-growth-phase cultures, followed by differential gene expression analysis using a LAB functional gene microarray. At low pH values, an increased expression of genes involved in peptide and amino acid metabolism was found as well as that of genes involved in plantaricin production and lipoteichoic acid biosynthesis. The results highlight cellular mechanisms that allowL. plantarumto function at a low environmental pH.


2016 ◽  
Vol 6 (1_suppl) ◽  
pp. s-0036-1582635-s-0036-1582635 ◽  
Author(s):  
Sibylle Grad ◽  
Ying Zhang ◽  
Olga Rozhnova ◽  
Elena Schelkunova ◽  
Mikhail Mikhailovsky ◽  
...  

2019 ◽  
Vol 20 (23) ◽  
pp. 6098 ◽  
Author(s):  
Amarinder Singh Thind ◽  
Kumar Parijat Tripathi ◽  
Mario Rosario Guarracino

The comparison of high throughput gene expression datasets obtained from different experimental conditions is a challenging task. It provides an opportunity to explore the cellular response to various biological events such as disease, environmental conditions, and drugs. There is a need for tools that allow the integration and analysis of such data. We developed the “RankerGUI pipeline”, a user-friendly web application for the biological community. It allows users to use various rank based statistical approaches for the comparison of full differential gene expression profiles between the same or different biological states obtained from different sources. The pipeline modules are an integration of various open-source packages, a few of which are modified for extended functionality. The main modules include rank rank hypergeometric overlap, enriched rank rank hypergeometric overlap and distance calculations. Additionally, preprocessing steps such as merging differential expression profiles of multiple independent studies can be added before running the main modules. Output plots show the strength, pattern, and trends among complete differential expression profiles. In this paper, we describe the various modules and functionalities of the developed pipeline. We also present a case study that demonstrates how the pipeline can be used for the comparison of differential expression profiles obtained from multiple platforms’ data of the Gene Expression Omnibus. Using these comparisons, we investigate gene expression patterns in kidney and lung cancers.


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